| CPC G06F 9/5027 (2013.01) [G06F 7/36 (2013.01)] | 14 Claims |

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1. A method of accelerating graph neural network (GNN) pre-processing, the method comprising:
performing, by a set-partitioning accelerator, radix sorting based on a vertex identification (VID) of an original graph in a coordinate list (COO) format to generate a COO array of a preset length;
merging, by a merger, the COO array of the preset length to generate one sorted COO array;
converting, by a converter, the one sorted COO array into a compressed sparse row (CSR) format to generate a graph in a CSR format;
performing, by a set-partitioning accelerator, uniform random sampling, to generate a sub-graph with a reduced degree of the graph in the CSR format; and
generating, by an embedding table generation unit, an embedding table corresponding to the sub-graph,
wherein when the merger is provided as a plurality of mergers, pipelining is performed among the plurality of mergers.
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